Bayesian Applications in Environmental and Ecological Studies with R and Stan

<p>Modern ecological and environmental sciences are dominated by observational data. As a result traditional statistical training often leaves scientists ill-prepared for the data analysis tasks they encounter in their work. Bayesian methods provide a more robust and flexible tool for data analysis as they enable information from different sources to be brought into the modelling process. <strong>Bayesian Applications in Evnironmental and Ecological Studies with R and Stan</strong> provides a Bayesian framework for model formulation parameter estimation and model evaluation in the context of analyzing environmental and ecological data.</p><p><strong>Features:</strong></p><ul> <li>An accessible overview of Bayesian methods in environmental and ecological studies</li> <li>Emphasizes the hypothetical deductive process particularly model formulation</li> <li>Necessary background material on Bayesian inference and Monte Carlo simulation</li> <li>Detailed case studies covering water quality monitoring and assessment ecosystem response to urbanization fisheries ecology and more</li> <li>Advanced chapter on Bayesian applications including Bayesian networks and a change point model</li> <li>Complete code for all examples along with the data used in the book are available via GitHub</li> </ul><p>The book is primarily aimed at graduate students and researchers in the environmental and ecological sciences as well as environmental management professionals. This is a group of people representing diverse subject matter fields who could benefit from the potential power and flexibility of Bayesian methods.</p>